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Statistical Evaluation of Diagnostic Test Performance for Avian Influenza Using Logistic Regression Modeling and ROC Curve Analysis

Egyptian Journal of Veterinary Sciences - EJVS • 2026
العودة
معلومات البحث
المؤلفون Esraa Reda Gouda, Sherif I Ramadan, Salah M Mohamed
الكلمات المفتاحية Avian Influenza, Diagnostic Accuracy, Reference standard, Likelihood ratios, Agreement Analysis.
المجلة العلمية Egyptian Journal of Veterinary Sciences - EJVS
الناشر الناشر National Information and Documentation Center (NIDOC), Academy of Scientific Research and Technology (ASRT)
المجلد 57
العدد 12
الصفحات 1-9
publication.type International
رابط البحث Open Link
المواد المرفقة Not Available
الملخص
Accurate evaluation of veterinary diagnostic tools is crucial for the surveillance and control of avian influenza (AI) in poultry populations. This study assesses the diagnostic accuracy of hemagglutination inhibition (HI) and postmortem examination (PM), using polymerase chain reaction (PCR) as the reference standard. A total of 132 poultry samples were analyzed. Cross-tabulation and chi-square analyses were used to evaluate associations with PCR-confirmed infection, and odds ratios (ORs) with 95% confidence intervals were calculated. Diagnostic performance was assessed using sensitivity, specificity, predictive values, likelihood ratios, diagnostic odds ratio (DOR), and Cohen’s kappa for agreement. HI demonstrated higher specificity (91.3%) but lower sensitivity (27.9%), while PM showed higher sensitivity (72.1%) but lower specificity (37.0%). The DOR for HI was 4.06, and for PM, it was 1.51, indicating limited discriminatory ability for both tests. Agreement with PCR was low for both HI (κ = 0.149) and PM (κ = 0.093). McNemar’s test revealed significant differences in detection rates between the two methods (p < 0.001). These findings suggest that while HI and PM provide valuable surveillance data, neither test alone is accurate enough to replace PCR as a confirmatory tool. A multi-metric diagnostic approach is recommended, with HI and PM serving as complementary tools, particularly in resource-limited settings where molecular diagnostics are not readily available, to support surveillance and outbreak control.
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